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ARTEMIS: attention-based retrieval with text-explicit matching implicit similarity
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| Ginger Delmas, Rafael Sampaio De Rezende, Gabriela Csurka, Diane Larlus |
| Tenth International Conference on Learning Representations (ICLR), virtual event, 25 - 29 April, 2022 |
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A multi-modal query, i.e. a query composed of an example image and a companion sentence that modifies it, is a very intuitive way to search for images of a particular fashion article. Previous attempts at tackling this complex task have mostly focused on learning to compose the visual and textual descriptors of the query elements in order to directly compare the resulting representation to those of the candidate fashion target images. Our approach departs from this strategy. We proposes two simple modules which draw inspiration from cross-modal retrieval and image search, respectively. These two research domains have been extensively studied and their successes, when combined, can be used to effectively tackle our task, which lies at the intersection of both families of approaches. We validate our method on several benchmarks with free-form text modifiers and obtain substantial performance improvements on several tasks.
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